Top Machine Learning Jobs in Krakow

Lead software engineering efforts for Samsara’s External Platform EMEA, building scalable distributed systems, APIs, reporting, administration, integrations, and business-critical infrastructure. Lead technical discussions, influence architecture and roadmap, deliver full-stack features, maintain production systems, and support customer-focused iteration. Mentor engineers, hire and develop high-performing teams, and contribute to machine learning-powered products and long-running projects.

Builds data engineering solutions for in-vehicle data quality, validation-drive automation, data triaging, and insights supporting hands-off urban driving. Responsibilities include developing APIs, cleaning and organizing raw and processed data, implementing analytics and machine learning solutions, and collaborating with engineering, product, and domain teams. The role involves cloud-based ETL and big-data systems connected to embedded driver-assistance technologies.

Processes investor transaction documents, maintains capital activity reports, completes AML requirements, prepares money movement notifications and wire instructions, and serves as a daily client contact. The role supports investor servicing operations, meets service-level deadlines, develops knowledge of allocations and performance calculations, mentors junior staff under supervision, and contributes to projects and ad hoc tasks.

Build, deploy, monitor, and improve production machine learning systems for customer and revenue use cases. Develop scalable data and ML pipelines, work with structured and unstructured data, apply modern ML and LLM techniques, and ensure model reliability through testing and validation. Collaborate with data engineers, product managers, and business stakeholders to deliver end-to-end solutions that improve business outcomes.

Lead GitLab’s company-wide strategy for autonomous, agentic software development workflows. Identify and validate AI opportunities across the SDLC, build prototypes and reference architectures, establish evaluation frameworks and safety controls, and drive internal adoption. Partner across Engineering, Product, Infrastructure, Security, Architecture, and Data and ML teams to scale reliable, observable, compliant agentic capabilities into customer-facing products. Mentor senior technical leaders and represent GitLab externally on AI-assisted development and productivity measurement.

Analyzes large datasets to identify platform performance and reliability issues, develops forecasting and early-warning systems, and builds software tools that automate analytical workflows. The role applies statistical analysis, machine learning, networking knowledge, and coding to diagnose content delivery challenges. It partners with Engineering, Operations, and Product teams to guide technology adoption and investment decisions. This is explicitly not a QA, DevOps, or Operations role.

Own the global B2B content strategy for enterprise audiences, creating website copy, advertising, whitepapers, case studies, thought leadership, social content, video scripts, and sales enablement materials. Build AI-assisted content workflows with prompt libraries, source-of-truth repositories, context engineering, quality controls, and human review. Partner with Product, Sales, and regional Marketing teams to communicate complex AI products and optimize content using performance data.

Develop computer vision and machine learning models that analyze biological and microscopy images to identify medical features and biomarkers. The role requires Python, image processing, and PyTorch or TensorFlow experience, along with independent problem-solving, strong communication, and collaboration across distributed international teams. The engineer will work remotely on an AI-driven MedTech diagnostic project with significant technical ownership.

Lead the technical vision, design, development, and deployment of AI-powered mobile and edge solutions across Android, iOS, and Windows. Build production-ready machine learning pipelines, AI services, device integrations, observability capabilities, and scalable mobile applications. Mentor engineers and collaborate with product, UX, architecture, and business teams. The role emphasizes IoT, embedded systems, edge AI, generative AI, computer vision, predictive analytics, and regulated-industry applications.

Explore, evaluate, and operationalize emerging AI methodologies, models, architectures, and technologies. Design experiments, benchmarks, evaluations, and proofs of concept; develop and productize generative, agentic, multimodal, and machine learning solutions; translate research into reusable enterprise capabilities; and collaborate with platform, data, product, architecture, and engineering teams to scale AI across Danaher.

Leads Danaher’s global AI Engineering, Integration and Operations organization, converting AI prototypes and capabilities into secure, scalable, production-grade solutions. Responsibilities include establishing engineering and operational practices, leading multidisciplinary teams, partnering with product and governance leaders, planning engineering capacity, and ensuring reliable deployment, support, adoption, and continuous improvement of enterprise AI solutions.

Develop machine learning and analytics solutions using large-scale datasets. Responsibilities include feature engineering, predictive modeling, workflow optimization, customer implementations, production deployments, stakeholder collaboration, technical training, and resolving data-related challenges. The role requires Python, PySpark, machine learning pipelines, MLflow or Airflow, statistical modeling, and strong communication skills, with preferred experience in fraud detection, risk analytics, compliance, cloud environments, and model monitoring.

Designs, develops, and scales autonomous AI agents and workflow orchestration solutions using LLM frameworks such as n8n. Builds rapid proofs of concept, integrates agents with enterprise CRM, ERP, and SaaS systems, establishes responsible AI governance, evaluates automation effectiveness, and trains internal teams on agentic AI adoption.

Build core components of a diagnostic and personalization platform: backend data pipelines, frontends, services for genomic data ingestion, ML model integration, APIs, and cloud infrastructure. Collaborate with product and ML teams, iterate on prototypes and MVPs, and make architectural decisions supporting scalability and reliability.

Owns full-cycle recruiting for commercial, operational, and technical roles across global markets. Responsibilities include sourcing passive candidates, building pipelines for hard-to-fill positions, advising hiring leaders, coordinating interviews and offers, maintaining accurate Greenhouse data, and improving hiring processes through systems thinking, data, AI, and automation.

Build BLP’s core software across infrastructure, backend, machine learning, and product extension platforms. Responsibilities include operating secure and observable cloud infrastructure, developing performant distributed systems, applying AI to business problems, and enabling customer process automation. The role emphasizes formal reasoning, correctness by construction, maintainable systems, type systems, and functional programming. Work is available onsite in Zurich or remotely within Europe.

Lead Business Analysis activities for Consumer Intelligence: shape and improve BA practices, drive demand intake and prioritization, maintain roadmap, apply agile and UAT best practices, coordinate cross-team delivery, and ensure alignment with business objectives and internal controls.

Develop and improve computer vision systems focused on aerial image recognition for a roofing technology platform. Build, train, evaluate, fine-tune, and deploy models for detection, segmentation, classification, and pattern recognition. Research and prototype modern vision, foundation, multimodal, and language-model solutions; optimize accuracy, reliability, and inference performance; prepare data pipelines; and identify product opportunities for AI. The role requires independent ownership of open-ended technical challenges from research through deployment.

Develop and deploy computer vision and machine learning systems for aerial image recognition in construction technology. Responsibilities include object detection, segmentation, classification, model training and optimization, rapid prototyping, multimodal AI experimentation, data pipeline development, and researching AI applications that improve product functionality and user experience.

Own the strategy, roadmap, execution, and business outcomes for MEDvidi’s AI Receptionist product. Lead cross-functional collaboration across Product, Engineering, Clinical, and Operations teams; improve conversational AI quality through experimentation, evaluation, analytics, and user feedback; define success metrics; and ensure safety, privacy, and reliability in regulated healthcare workflows.

Own the Vault product roadmap and lifecycle for a sports media asset platform. Lead discovery with customers, define solutions for content ingest, storage, integrations, AI enrichment, metadata, search, rights, and asset monetization. Partner closely with engineering, sales, and customer success, attend customer events, and prioritize product bets that help sports organizations maximize the value of extensive media archives.

Corti is seeking passionate individuals to join their talent community, shaping the future of healthcare through AI technologies. Opportunities include roles in AI technology, machine learning, and software development, focusing on reducing errors and improving patient outcomes.

Design, build, deploy, and evaluate production-grade generative AI applications using foundation models and LLMs. Develop RAG systems, AI agents, fine-tuned models, evaluation pipelines, and high-quality datasets for financial workflows. Optimize latency and cost while implementing scalable deployment, monitoring, safety guardrails, and responsible AI practices. Collaborate cross-functionally to deliver AI-powered solutions for finance and accounting teams.

Lead data strategy, architecture, governance, quality, compliance, and technology adoption. Translate stakeholder needs into scalable data initiatives, support advanced analytics and AI/ML, promote data literacy, and guide cross-functional teams toward data-driven decision-making.

Design and develop scalable, high-quality backend systems for traffic automated road closure detection, handling the full software development lifecycle.